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Record W4391322650 · doi:10.3389/fnhum.2023.1334264

Patricia Goldman-Rakic: a pioneer and leader in frontal lobe research

2024· article· en· W4391322650 on OpenAlexaff
Bryan Kolb

Bibliographic record

VenueFrontiers in Human Neuroscience · 2024
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsFrontal lobePrefrontal cortexPsychologyNeuroscienceFrontal cortexCognitionWorking memory

Abstract

fetched live from OpenAlex

Our understanding of the organization of the frontal cortex can be traced back to the experimental studies in the late 1800s by Fritsch and Hitzig on the frontal cortex of dogs and the frontal cortex of monkeys by Ferrier. These studies and many other studies that followed focused on motor functions, but halfway through the 20th century, very little was understood about the role of the frontal lobe in the control of other functions, and it was generally thought that the frontal lobe did not play a significant role in cognition. One result was that studies of cortical functions in cognition were carried out largely on parietal and temporal cortical regions with surprisingly little interest in the frontal lobe. The first systematic studies of the effects of prefrontal lesions on non-human primates began around 1950, especially by Rosvold and Mishkin in the Laboratory of Psychology at the National Institute of Mental Health (NIMH) in the United States. With her background in development, Pat Goldman joined this laboratory in 1965 and began an examination of the effects of prefrontal lobectomy on behavior in infant rhesus monkeys, both during development and later as the animals grew into adulthood. Her developmental studies were groundbreaking as they demonstrated that the effects of early prefrontal lesions varied with precise age (including prenatal), precise lesion location, behaviors measured, and age at assessment. She also began in parallel extensive studies of the role of the prefrontal cortex for a range of functions (especially working memory) in adult monkeys, which led to an examination of factors that influenced functional outcomes after injury or disease. This research was critical in helping to identify the significant role of the prefrontal cortex in cognition in both normal brains and neurological diseases such as schizophrenia. Her pioneering study demonstrating the role of the prefrontal cortex in cognition led to a remarkable increase in the number of researchers studying prefrontal functions in both non-human primates and rodents. This review will chronicle the key findings in her 35+ years studying the prefrontal cortex and illustrate the course she set for generations to follow.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.006
Scholarly communication0.0030.005
Open science0.0020.002
Research integrity0.0030.011
Insufficient payload (model declined to judge)0.0040.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.112
GPT teacher head0.358
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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